Predictive modeling of outcomes in acute leukemia patients undergoing allogeneic hematopoietic stem cell transplantation using machine learning techniques.

Journal: Leukemia research
PMID: 39591832

Abstract

BACKGROUND: Leukemia necessitates continuous research for effective therapeutic techniques. Acute leukemia (AL) patients undergoing allogeneic hematopoietic stem cell transplantation (allo-HSCT) focus on key outcomes such as overall survival (OS), relapse, and graft-versus-host disease (GVHD).

Authors

  • Maedeh Rouzbahani
    Tehran University of Medical Sciences, School of Medicine, Tehran, Iran; Advanced Diagnostic and Interventional Radiology Research Center (ADIR) Tehran University of Medical Science, Tehran, Iran. Electronic address: maederouzbahani@gmail.com.
  • Seyed Amirhossein Mousavi
    Department of Medical Physics, Kashan University of Medical Sciences, Kashan, Iran. Electronic address: amir.h.musavi1998@gmail.com.
  • Ghasem Hajianfar
    Rajaie Cardiovascular Medical and Research Center, Iran University of Medical Science, Tehran, Iran.
  • Ali Ghanaati
    Shahid Beheshti University of Medical Sciences, School of Allied Medical Sciences, Tehran, Iran. Electronic address: ghanaati78@gmail.com.
  • Mohammad Vaezi
    Tehran University of Medical Sciences, School of Medicine, Tehran, Iran. Electronic address: vaezi.mohamad@yahoo.com.
  • Ardeshir Ghavamzadeh
    Tehran University of Medical Sciences, School of Medicine, Tehran, Iran. Electronic address: ghavamza@gmail.com.
  • Maryam Barkhordar
    Cell Therapy and Hematopoietic Stem Cell Transplantation Research Center, Research Institute for Oncology, Hematology and Cell Therapy, Iran.

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